Jazzer's JUnit integration is described on the main readme page at JUnit 5. This document will go into more details about more specific aspects of the integration.
Classic Jazzer fuzz tests expect a single parameter of type FuzzedDataProvider
or byte[]
, which can be used to
create further inputs required by the function under test. This can get quite cumbersome for tests that require multiple
or complex inputs.
To address this issue, Jazzer adds the ability to expect any number of parameters of primitive and, limited, object types. The underlying functionality, called "mutation framework", will create and mutate these parameters in a type specific manner.
Type information enable the fuzzer to directly generate valid input and not only a low level byte representation, which could easily break during manual object creation in the fuzz test and result in inefficient retries.
The mutation framework is designed in an extensible and composable way, so that type specific mutation logic is encapsulated in dedicated classes, and can easily and automatically be composed into mutators for complex types. Furthermore, new mutators for currently unsupported or custom types are directly integrated into the mutation framework and used during generation of mutators for other types.
The mutation framework integrates with the underlying fuzzing engine and ensures stability of saved findings and corpus entries, so that changes in the mutation framework itself or the mutation logic of specific mutators don't invalidate existing findings or corpus entries.
The mutation framework is located in the com.code_intelligence.jazzer.mutation
package.
Note: If a fuzz function still expects a single FuzzedDataProvider
or byte[]
parameter, the mutation framework
will not be used!
The example below shows how to use complex data types in a fuzz test. Any supported type can be used as a parameter of a fuzz test. The mutation framework will automatically create and mutate the parameters accordingly.
record SimpleTypesRecord(boolean bar, int baz) {
}
@FuzzTest
public void testSimpleTypeRecord(SimpleTypesRecord record) {
doSomethingWithRecord(record);
}
Type specific mutations are located in the com.code_intelligence.jazzer.mutation.mutator
package.
Mutators are free to implement mutations in any way they see fit, e.g. the integral type mutator can perform bit flips,
random walks, pseudo random number picks between specified min
and max
values, or fall back to the underlying
fuzzing engine mutation.
Mutators automatically compose into mutators for complex types, e.g. a list mutator will use the mutator for the list element type to generate and mutate list elements and so on. If an unsupported type is encountered no mutator can be created.
Currently supported types are:
Mutator | Type(s) | Notes |
---|---|---|
Boolean | boolean , Boolean |
|
Integral | byte , Byte , short , Short , int , Int , long , Long |
|
Floating point | float , Float , double , Double |
|
String | java.lang.String |
|
Enum | java.lang.Enum |
|
InputStream | java.io.InputStream |
|
Time | java.time.LocalDate , java.time.LocalDateTime , java.time.LocalTime , java.time.ZonedDateTime |
|
Array | Arrays holding any other supported type (e.g. byte[] , Integer[] , Map[] , String[] , etc.) |
|
List | java.util.List |
|
Map | java.util.Map |
|
Record | java.lang.Record |
Arbitrary Java Records, if supported by JVM version |
Setter-based JavaBean | Any class adhering to the JavaBeans Spec, see JavaBeans Support for details | |
Constructor-based JavaBean | Any class adhering to the JavaBeans Spec, see JavaBeans Support for details | |
Constructor-based Java Classes | Any class requiring constructor parameters, but not offering getter methods, see constructor-based classes for details | |
Builder | See Builder pattern support for details | |
FuzzedDataProvider | com.code_intelligence.jazzer.api.FuzzedDataProvider |
|
Protobuf | com.google.protobuf.Message , com.google.protobuf.Message.Builder , com.google.protobuf.ByteString |
Classes generated by the Protobuf toolchain |
Nullable | Any reference type will occasionally be set to null |
It is sometimes helpful to provide additional information about the Fuzz Test parameters, e.g. to specify the range of integers, or the maximum length of a string. This is done using annotations directly on the parameters.
Note: Annotations are used on best effort basis, meaning that the fuzzer will try to honor specified constraints, but can not guarantee it.
All annotations reside in the com.code_intelligence.jazzer.mutation.annotation
package.
Annotation | Applies To | Notes |
---|---|---|
@Ascii |
java.lang.String |
String should only contain ASCII characters |
@InRange |
byte , Byte , short , Short , int , Int , long , Long |
Specifies min and max values of generated integrals |
@InRangeFloat |
float , Float |
Specifies min and max values of generated floats |
@InRangeDouble |
double , Double |
Specifies min and max values of generated doubles |
@NotNull |
Specifies that a reference type should not be null |
|
@WithLength |
byte[] |
Specifies the length of the generated byte array |
@WithUtf8Length |
java.lang.String |
Specifies the length of the generated string in UTF-8 bytes, see annotation Javadoc for further information |
@WithSize |
java.util.List , java.util.Map |
Specifies the size of the generated collection |
@UrlSegment |
java.lang.String |
String should only contain valid URL segment characters |
The example below shows how Fuzz Test parameters can be annotated to provide additional information to the mutation framework.
record SimpleTypesRecord(boolean bar, int baz) {}
@FuzzTest
public void testSimpleTypeRecord(@NotNull @WithSize(min = 3, max = 100) List<SimpleTypesRecord> records) {
doSomethingWithRecord(record);
}
Often, annotations should be applied to a type and all it's nested component
types. This use-case is supported by the annotation's constraint
property. It
can be set to PropertyConstraint.RECURSIVE
so that the annotation is
propagated down to all subcomponent types.
All above-mentioned annotations support this feature.
For example, if a Fuzz Test expects a List
of List
of Integer
as
parameter, and both the lists and their values must not be null
, the
annotation @NotNull(constraint = PropertyConstraint.RECURSIVE)
could be added
on the root type.
@FuzzTest
public void fuzz(@NotNull(constraint = PropertyConstraint.RECURSIVE) List<List<Integer>> list) {
// list is not null and does not contain null entries on any level
assertDeepNotNull(list);
}
Jazzer can generate and mutate instances of classes adhering to the JavaBeans Spec.
To serialize and deserialize Java objects to and from corpus entries, Jazzer can use setters, constructors and getters to pass values to a JavaBean and extract them back out from it.
The setter-based approach requires a class to provide a default constructor with
no arguments. The corresponding methods are looked up by name and must adhere to
the JavaBeans Spec naming convention, meaning setXX
and getXX
/isXX
methods
for property XX
. A JavaBean can have additional getters corresponding to
computed properties, but it is required that all setters have a corresponding
getter.
public static class FooBean {
private String foo;
public String getFoo() {
return foo;
}
public void setFoo(String foo) {
this.foo = foo;
}
}
@FuzzTest
public void testFooBean(FooBean fooBean) {
// ...
}
The constructor-based approach requires a class to provide a constructor with arguments. If multiple constructors are available, the one with the most supported parameters will be preferred.
The lookup of matching getters relies on the Java bean's property names. As a
class can have further properties or internal states, this approach relies on
the constructor parameter names. Since parameter names are not always available
at runtime, they explicitly have to be compiled into the class file with the use
of the JavaBeans @ConstructorProperties
annotation, to specify property names
explicitly.
public static class PropertyNamesBean {
private final String bar;
public PropertyNamesBean(String bar) {
this.bar = bar;
}
public String getBar() {
return bar;
}
}
public static class ConstructorPropertiesBean {
private final String foo;
@ConstructorProperties({"bar"})
public PropertyNamesBean(String foo) {
this.bar = foo;
}
public String getBar() {
return foo;
}
}
public static class FallbackTypeBean {
private final String foo;
public PropertyNamesBean(String foo) {
this.bar = foo;
}
public String getSomething() {
return foo;
}
}
@FuzzTest
public void testBeans(PropertyNamesBean propertyNamesBean, ConstructorPropertiesBean constructorPropertiesBean, FallbackTypeBean fallbackTypeBean) {
// ...
}
Jazzer can generate and mutate instances of classes that build up their internal state via constructor parameters, and, in contrast to JavaBeans, don't offer getter methods.
The following class would fall into this category:
class ImmutableClassTest {
static class ImmutableClass {
private final int bar;
public ImmutableClass(int foo) {
this.bar = foo * 2;
}
String barAsString() {
return String.valueOf(bar);
}
}
@FuzzTest
void fuzzImmutableClassFunction(ImmutableClass immutableClass) {
if (immutableClass != null && "42".equals(immutableClass.barAsString())) {
throw new RuntimeException("42!");
}
}
}
The builder pattern is a common design pattern to simplify the construction of complex objects.
- A common implementation gathers all required parameters in the
builder
and passes them to the constructor of the target class. - Another approach is used for
builder
s supporting a nested type hierarchy in the target class. In this situation thebuilder
itself is passed into the constructor of the target class.
Note: These pattern are generated by the commonly used
Lombok @Builder
and @SuperBuilder
annotations.
The examples below use Lombok to generate
appropriate builder
classes:
class SimpleClassFuzzTests {
@Builder
static class SimpleClass {
String foo;
List<Integer> bar;
boolean baz;
}
@FuzzTest
void fuzzSimpleClassFunction(@NotNull SimpleClass simpleClass) {
someFunctionToFuzz(simpleClass);
}
}
class SimpleClassFuzzTests {
@SuperBuilder
static class ParentClass {
String foo;
}
@SuperBuilder
static class ChildClass extends ParentClass {
List<Integer> bar;
}
@FuzzTest
void fuzzChildClassFunction(@NotNull ChildClass childClass) {
someChildFunctionToFuzz(childClass);
}
}
The FuzzedDataProvider
is an alternative approach commonly used in programming
languages like C and C++. It provides an intuitive interface to deconstruct
fuzzer input with type-specific functions, e.g. consumeString
,
consumeBoolean
or consumeInt
. Jazzer's Java implementation follows the
FuzzedDataProvider
of the LLVM Project.
This programmatic approach offers very fine-grained control, but requires much more effort to build up needed data structures.
Below is an example of a simple Fuzz Test using the FuzzedDataProvider
:
import com.code_intelligence.jazzer.api.FuzzedDataProvider;
import com.code_intelligence.jazzer.junit.FuzzTest;
class ParserTests {
@Test
void unitTest() {
assertEquals("foobar", SomeScheme.decode(SomeScheme.encode("foobar")));
}
@FuzzTest
void fuzzTest(FuzzedDataProvider data) {
String input = data.consumeRemainingAsString();
assertEquals(input, SomeScheme.decode(SomeScheme.encode(input)));
}
}
Jazzer's JUnit integration starts from
the FuzzTest
annotation. As mentioned in the
annotation's javadoc, our integration runs in one of two modes: fuzzing and regression. Fuzzing mode will generate new
inputs to feed into the tests to find new issues and regression mode will run the tests against previous findings, no
fuzzing is done. The main entrypoints for the actual integration code are found in two of the annotations
on FuzzTest
: @ArgumentsSource(FuzzTestArgumentsProvider.class)
and @ExtendsWith(FuzzTestExtensions.class)
.
Because these same files and functions are involved in two mostly separate sets of functionality, this will look at the
flow of the different methods involved in integrating with JUnit in fuzzing mode (when JAZZER_FUZZ
is set to a truthy
value (true
, 1
, yes
)) and in regression mode (when JAZZER_FUZZ
is not set) separately.
JUnit will call the following methods for each test marked with FuzzTest
.
The first call to this test will determine if the test should be run at all. In fuzzing mode, we only allow one test to be run due to global state in libfuzzer that would mean multiple tests would interfere with each other. Jazzer will accept the first fuzz test that is checked as the test to be run. It will cache which test it has seen first and return that test as enabled.
If this returns that a test is disabled, JUnit will not run the rest of these methods for this test and instead skip to the next one.
This will configure the fuzzing agent to set up code instrumentation, instantiate a FuzzTestExecutor
and put it into
JUnit's extensionContext
, then create a stream of a single empty argument set. As the comment mentions, this is so
that JUnit will actually execute the test but the argument will not be used.
This will be called for each argument set for the current test. In fuzzing mode, there will only be the single empty argument set which will be enabled.
This will call invocation.skip()
which prevents invoking the test function with the default set of
arguments provideArguments
created. It will instead extract the FuzzTestExecutor
instance from
the extensionContext
and then calls FuzzTestExecutor#execute
which creates a FuzzTargetRunner
to run the actual
fuzzing.
Crashes are saved in resources/<package>/<test file name>Inputs/<test method name>
and results that are interesting to
libfuzzer are saved in .cifuzz-corpus
.
Similar to fuzzing mode, JUnit will call these methods for each test marked with FuzzTest
.
This checks if the given test should be run at all. In regression mode, all tests are run so this will always return enabled.
This will configure the fuzzing agent as in fuzzing mode, then gather test cases to run from the following sources:
- A default argument set of just an empty input
- A set of arguments from the associated resources directory
- If a
.cifuzz-corpus
directory exists, relevant entries from that are added as well
Prior to returning, the stream of test cases is put through adaptInputsForFuzzTest
to turn the raw bytes from the
files into the actual types to be given to the tested function.
The tests from the resources directory are gathered by walkInputs
. This will look for inputs in two places:
resources/<package>/<test class name>Inputs
- files found directly within this directory will be used as inputs for any tests within this class. This allows for easy sharing of corpus entries. Jazzer does not automatically put entries here, instead a human will need to decide a finding should be shared and manually move it.resources/<package>/<test class name>Inputs/<test method name>
- files found in this directory and any directory under it are used as inputs for only the test of the same name.
JUnit will use the file's name as the name of the test case for its reporting. It also accepts .jar files where it will search with the given directory in the jar.
The corpus kept in .cifuzz-corpus/<test class name>/<test method name>
holds any inputs that libfuzzer found worth
saving and not necessarily just inputs that caused a crash. Jazzer is able to set the directory but the contents of
these directories are managed entirely by libfuzzer. Unlike with the resources test inputs above, this will not look
in .cifuzz-corpus/<test class name>
for shared test cases. This is a limitation of libfuzzer.
This will run once per argument set returned by provideArguments
for this test. All argument sets will return as
enabled.
This will run for each individual test case for each fuzz test and will mostly just allow the test function to proceed with the provided arguments. Prior to the call to the test, it will enable the agent's hooks and then disable them afterward. It will also check for and report any findings from Jazzer to JUnit.
Below are two sequence diagrams for how JUnit calls evaluateExecutionConditions
and provideArguments
in fuzzing and
regression mode. These diagrams ignore interceptTestTemplateMethod
for brevity as its behavior and place in the
sequence is more clear.